title: Automatic segmentation of cardiac MRI cines validated for long axis views.
abstract: Segmentation of cardiac magnetic resonance imaging is considered an important application in clinical practice. An automatic algorithm is proposed for segmentation of both endocardial and epicardial boundaries, in long-axis views. The data consisted of 126 patients, yielding 1008 traces. Estimated clinical parameters were highly correlated to gold standard measurements. The error between the automatic tracing and the gold standard was not significantly different than the error between two manual observers. In conclusion, a tool for segmenting the myocardial boundaries in the long-axis views is proposed, which works well, as demonstrated by the validation performed using a clinical dataset.
authors.affiliation: Faculty of Biomedical Engineering, Technion-IIT Technion City, Haifa 32000, Israel. Electronic address: yossit@tx.technion.ac.il.
authors.forename: Yossi
authors.initials: Y
authors.lastname: Tsadok
authors.forename: Yael
authors.initials: Y
authors.lastname: Petrank
authors.forename: Sebastian
authors.initials: S
authors.lastname: Sarvari
authors.forename: Thor
authors.initials: T
authors.lastname: Edvardsen
authors.forename: Dan
authors.initials: D
authors.lastname: Adam
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D019028:Magnetic Resonance Imaging, Cine / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D018487:Ventricular Dysfunction, Left / Q000473:pathology*
keywords: Cardiac magnetic resonance imaging (cMRI); Image registration; Image segmentation; Long-axis views; Myocardial segmentation